Gaussian Process Regression Applied to VRLA Battery Voltage Prediction in Photovoltaic Off-Grid Systems
DOI:
https://doi.org/10.26754/jji-i3a.201802826Resumen
This study addresses the use of GPR techniques for VRLA battery voltage prediction purposes in PV off-grid systems. The goal is to know whether the system is able to endure a predictable power consumption pattern without running out of energy. Two approaches are considered: sample based prediction and pattern-based forecasting.
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Publicado
2018-05-25
Cómo citar
Sanz Gorrachategui, I., Bernal Ruiz, C., Bono Nuez, A., Pajovic, M., & Martínez Ruata, G. (2018). Gaussian Process Regression Applied to VRLA Battery Voltage Prediction in Photovoltaic Off-Grid Systems. Jornada De Jóvenes Investigadores Del I3A, 6. https://doi.org/10.26754/jji-i3a.201802826
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Sección
Artículos (Tecnologías Industriales)
